OPSR: Ordinal Probit Switching Regression
Estimates ordinal probit switching regression models - a Heckman
type selection model with an ordinal selection and continuous outcomes.
Different model specifications are allowed for each treatment/regime. For
more details on the method, see Wang & Mokhtarian (2024) <doi:10.1016/j.tra.2024.104072>
or Chiburis & Lokshin (2007) <doi:10.1177/1536867X0700700202>.
Version: |
0.1.2 |
Depends: |
R (≥ 3.5.0) |
Imports: |
car, Formula, MASS, maxLik, methods, mvtnorm, Rcpp, Rdpack (≥
0.7), sandwich, stats, texreg, utils |
LinkingTo: |
Rcpp, RcppArmadillo |
Suggests: |
testthat (≥ 3.0.0) |
Published: |
2024-11-01 |
DOI: |
10.32614/CRAN.package.OPSR |
Author: |
Daniel Heimgartner
[aut, cre,
cph],
Xinyi Wang [aut] |
Maintainer: |
Daniel Heimgartner <d.heimgartners at gmail.com> |
BugReports: |
https://github.com/dheimgartner/OPSR/issues |
License: |
GPL (≥ 3) |
URL: |
https://github.com/dheimgartner/OPSR |
NeedsCompilation: |
yes |
Citation: |
OPSR citation info |
Materials: |
README NEWS |
CRAN checks: |
OPSR results |
Documentation:
Downloads:
Linking:
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